Backgrounds <p><i>Streptococcus suis</i> is an emerging zoonotic bacterial disease with increasing prevalence in the human population and is one of the most important bacterial infections in pig husbandry. There is still a lack of a thorough understanding of <i>S. suis</i> metabolism and the connection between metabolism and virulence.</p> Results <p>A genome-scale metabolic model <i>i</i>NX525, which included 525 genes, 708 metabolites, and 818 reactions, was manually constructed with a 74% overall MEMOTE score. The flux balance analysis results of the model exhibited good agreement with growth phenotypes under different nutrient conditions and genetic disturbances. The model predictions aligned with 71.6%, 76.3%, and 79.6% of the gene essentiality predictions from three mutant screens. The model was then used to analyze virulence factors and related synthetic pathways. One hundred and thirty-one virulence-linked genes were found by comparing to virulence factor databases, and among them, seventy-nine virulence-linked genes were in 167 metabolic reactions in model <i>i</i>NX525. One hundred and one of the metabolic genes were predicted to affect the formation of nine virulence-linked small molecules. Complex interrelationships between growth- and virulence-associated pathways were evaluated, and 26 genes were found to be essential for both cell growth and virulence factor production. Among these, eight enzymes and metabolites were identified as antibacterial drug targets, focusing on the biosynthesis of capsular polysaccharides and peptidoglycans.</p> Conclusion <p>Overall, the metabolic model <i>i</i>NX525 provides a high-quality platform for systematic elucidation of the metabolism of <i>S. suis</i>.</p>

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Reconstruction and application of a genome-scale metabolic model for Streptococcus suis

  • Nan Xu,
  • Jiaqi Kang,
  • Chengkun Zheng,
  • Linyao Zhou,
  • Cong Gao,
  • Minliang Guo

摘要

Backgrounds

Streptococcus suis is an emerging zoonotic bacterial disease with increasing prevalence in the human population and is one of the most important bacterial infections in pig husbandry. There is still a lack of a thorough understanding of S. suis metabolism and the connection between metabolism and virulence.

Results

A genome-scale metabolic model iNX525, which included 525 genes, 708 metabolites, and 818 reactions, was manually constructed with a 74% overall MEMOTE score. The flux balance analysis results of the model exhibited good agreement with growth phenotypes under different nutrient conditions and genetic disturbances. The model predictions aligned with 71.6%, 76.3%, and 79.6% of the gene essentiality predictions from three mutant screens. The model was then used to analyze virulence factors and related synthetic pathways. One hundred and thirty-one virulence-linked genes were found by comparing to virulence factor databases, and among them, seventy-nine virulence-linked genes were in 167 metabolic reactions in model iNX525. One hundred and one of the metabolic genes were predicted to affect the formation of nine virulence-linked small molecules. Complex interrelationships between growth- and virulence-associated pathways were evaluated, and 26 genes were found to be essential for both cell growth and virulence factor production. Among these, eight enzymes and metabolites were identified as antibacterial drug targets, focusing on the biosynthesis of capsular polysaccharides and peptidoglycans.

Conclusion

Overall, the metabolic model iNX525 provides a high-quality platform for systematic elucidation of the metabolism of S. suis.